Function reference • readr

Read rectangular files These functions parse rectangular files (like csv or fixed-width format) into tibbles. They specify the overall structure of the file, and how each line is divided up into fields.
`read_delim()` `read_csv()` `read_csv2()` `read_tsv()`	Read a delimited file (including csv & tsv) into a tibble
`read_fwf()` `fwf_empty()` `fwf_widths()` `fwf_positions()` `fwf_cols()`	Read a fixed width file into a tibble
`read_log()`	Read common/combined log file into a tibble
`read_table()` `read_table2()`	Read whitespace-separated columns into a tibble
Column specification The column specification describes how each column is parsed from a character vector in to a more specific data type. readr does make an educated guess about the type of each column, but you’ll need override those guesses when it gets them wrong.
`problems()` `stop_for_problems()`	Retrieve parsing problems
`cols()` `cols_only()`	Create column specification
`cols_condense()` `spec()`	Examine the column specifications for a data frame
`spec_delim()` `spec_csv()` `spec_csv2()` `spec_tsv()` `spec_table()` `spec_table2()`	Generate a column specification
Column parsers Column parsers define how a single column is parsed, or a parse a single vector. Each parser comes in two forms: `parse_xxx()` which is used to parse vectors that already exist in R and `col_xxx()` which is used to parse vectors as they are loaded by a `read_xxx()` function.
`parse_logical()` `parse_integer()` `parse_double()` `parse_character()` `col_logical()` `col_integer()` `col_double()` `col_character()`	Parse logicals, integers, and reals
`parse_datetime()` `parse_date()` `parse_time()` `col_datetime()` `col_date()` `col_time()`	Parse date/times
`parse_factor()` `col_factor()`	Parse factors
`parse_guess()` `col_guess()` `guess_parser()`	Parse using the "best" type
`parse_number()` `col_number()`	Parse numbers, flexibly
`col_skip()`	Skip a column
Locale controls The “locale” controls all options that vary from country-to-country or language-to-language. This includes things like the character used as the decimal mark, the names of days of the week, and the encoding. See `vignette("locales")` for more details.
`locale()` `default_locale()`	Create locales
`date_names()` `date_names_lang()` `date_names_langs()`	Create or retrieve date names
Write rectangular files Despite its name, readr also provides a number of functions to write data frames to disk, or to convert them to in-memory strings.
`format_delim()` `format_csv()` `format_csv2()` `format_tsv()`	Convert a data frame to a delimited string
`write_delim()` `write_csv()` `write_csv2()` `write_excel_csv()` `write_excel_csv2()` `write_tsv()`	Write a data frame to a delimited file
Low-level IO and debugging tools These functions can be used with non-rectangular files, binary data, and to help debug rectangular files that fail to parse.
`read_file()` `read_file_raw()` `write_file()`	Read/write a complete file
`read_lines()` `read_lines_raw()` `write_lines()`	Read/write lines to/from a file
`count_fields()`	Count the number of fields in each line of a file
`guess_encoding()`	Guess encoding of file
`type_convert()`	Re-convert character columns in existing data frame
`readr_example()`	Get path to readr example
`clipboard()`	Returns values from the clipboard
Chunked API The chunked API allows you to read in files that are larger than memory, processing a chunk at a time. The API experimental: please try it out but be aware that it may change in the future.
`callback`	Callback classes
`read_delim_chunked()` `read_csv_chunked()` `read_csv2_chunked()` `read_tsv_chunked()`	Read a delimited file by chunks
`read_lines_chunked()` `read_lines_raw_chunked()`	Read lines from a file or string by chunk.

Reference

Read rectangular files

Column specification

Column parsers

Locale controls

Write rectangular files

Low-level IO and debugging tools

Chunked API

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